Hallucinations without delusions in patients with first-episode psychosis: Clinical correlates and implications for pathophysiological models

2016 ◽  
Vol 33 (S1) ◽  
pp. S32-S32
Author(s):  
I. Melle
Keyword(s):  
Negative Symptoms ◽  
Clinical Symptoms ◽  
Age At Onset ◽  
Diagnostic Interview ◽  
Clinical Profile ◽  
First Episode ◽  
Schizophrenia Spectrum Disorders ◽  
Schizophrenia Spectrum ◽  
Spectrum Disorders ◽  
Competing Interest

IntroductionThe symptomatic distribution in schizophrenia spectrum disorder is heterogeneous. Patients may experience hallucinations, delusions and combinations thereof, in addition to disorganized and negative symptoms. We have previously found that patients with monosymptomatic hallucinations exhibited a different clinical profile than patients with monosymptomatic delusions or combinations of the two; with an earlier age at onset and more suicidal symptoms.AimsTo replicate findings in a new group of patients with schizophrenia spectrum disorders.MethodsA total of 421 consecutive patients with schizophrenia spectrum disorders were included into the study. They were comprehensively assessed by specifically trained psychiatrists or clinical psychologists; using the SCID for DSM-IV for diagnostic purposes, the PANSS to assess current clinical symptoms and CDSS to assess current depression. Lifetime presence of different symptom types was ascertained during the diagnostic interview.ResultsA total of 346 (82%) had experienced both hallucinations and delusion, 63 (15%) had experienced delusions without hallucinations, 10 (2.5%) had experienced hallucinations without delusions and 2 patients (0.5%) had neither but experienced negative and severely disorganized symptoms. Contrary to hypothesis, we did not find any statistically significant differences in age at onset and in clinical symptoms (including suicidality) between these groups. We also did not find any differences in the type of hallucinatory experiences between hallucinating groups.ConclusionsIn a new sample of patients, we did not replicate previous findings of a different clinical profile in patients with monosymptomatic hallucinations. This type of psychotic disorder is relatively rare, which might pose a problem concerning statistical strength.Disclosure of interestThe author has not supplied his declaration of competing interest.

Measuring Motivation in Patients with Schizophrenia with Apathy Evaluation Scale (AES). Pilot Study of the Russian Version

2017 ◽  
Vol 41 (S1) ◽  
pp. S274-S274 ◽  
Author(s):  
M. Minyaycheva ◽  
K. Kiselnikova ◽  
L. Movina ◽  
I. Gladyshev ◽  
O. Papsuev
Keyword(s):  
Negative Symptoms ◽  
Psychosocial Treatment ◽  
Strong Correlations ◽  
Schizophrenia Spectrum Disorders ◽  
Russian Version ◽  
Schizophrenia Spectrum ◽  
Psychometric Tool ◽  
Spectrum Disorders ◽  
Competing Interest ◽  
Positive Correlations

IntroductionReduction of mental productivity and motivation in patients with schizophrenia is one of the core features of negative symptoms of schizophrenia spectrum disorders. Lack of motivation affects social functioning and outcomes, reduces effects of psychosocial treatment and rehabilitation.ObjectivesTo research AES abilities in measuring motivation in patients with schizophrenia spectrum disorders. The aim of the study was to investigate correlations of Russian translation of clinician-rated and self-rated versions with PANSS amotivation subscale and negative subscale items.MethodsFifty patients with schizophrenia spectrum disorders were recruited to participate in the study and were assessed with PANSS, AES-C and AES-S by trained raters. Only patients in “stabilized” state that met inclusion criteria of PANSS total score ≤ 80 points were eligible for consecutive AES assessment.ResultsOverall, moderate positive correlations were established between AES-C and PANSS amotivation subscale N2 and N4 items, N6 item and total PANSS negative subscale. No significant correlations with G16 item were registered. AES-C and AES-S versions also showed positive Spearman correlations (r = 0.43; P < 0.05), while no correlations between AES-S and amotivation PANSS items were registered.DiscussionModerately strong correlations between AES-C and PANSS N2, N4 and N6 items show feasibility of AES-C version in terms of measuring motivation in patients with schizophrenia spectrum disorders. Results of AES-S analysis demonstrate certain problems in patients’ abilities in self-assessing motivation. Patients with prevailing paranoid syndrome showed poorer results in AES-S scores.ConclusionsAES-C is a sensitive psychometric tool with good properties in measuring amotivation in patients with schizophrenia.Disclosure of interestThe authors have not supplied their declaration of competing interest.

The Relationship between Negative Symptoms and Both Emotion Management and Non-social Cognition in Schizophrenia Spectrum Disorders

2020 ◽  
pp. 1-13
Author(s):  
Caitlin O. B. Yolland ◽  
Sean P. Carruthers ◽  
Wei Lin Toh ◽  
Erica Neill ◽  
Philip J. Sumner ◽  
...  
Keyword(s):  
Social Cognition ◽  
Negative Symptoms ◽  
Clinical Symptoms ◽  
Hierarchical Cluster ◽  
Emotion Management ◽  
Schizophrenia Spectrum Disorders ◽  
Targeted Interventions ◽  
Schizophrenia Spectrum ◽  
Spectrum Disorders ◽  
The Relationship

Abstract Objective: There is ongoing debate regarding the relationship between clinical symptoms and cognition in schizophrenia spectrum disorders (SSD). The present study aimed to explore the potential relationships between symptoms, with an emphasis on negative symptoms, and social and non-social cognition. Method: Hierarchical cluster analysis with k-means optimisation was conducted to characterise clinical subgroups using the Scale for the Assessment of Negative Symptoms and Scale for the Assessment of Positive Symptoms in n = 130 SSD participants. Emergent clusters were compared on the MATRICS Consensus Cognitive Battery, which measures non-social cognition and emotion management as well as demographic and clinical variables. Spearman’s correlations were then used to investigate potential relationships between specific negative symptoms and emotion management and non-social cognition. Results: Four distinct clinical subgroups were identified: 1. high hallucinations, 2. mixed symptoms, 3. high negative symptoms, and 4. relatively asymptomatic. The high negative symptom subgroup was found to have significantly poorer emotion management than the high hallucination and relatively asymptomatic subgroups. No further differences between subgroups were observed. Correlation analyses revealed avolition-apathy and anhedonia-asociality were negatively correlated with emotion management, but not non-social cognition. Affective flattening and alogia were not associated with either emotion management or non-social cognition. Conclusions: The present study identified associations between negative symptoms and emotion management within social cognition, but no domains of non-social cognition. This relationship may be specific to motivation, anhedonia and apathy, but not expressive deficits. This suggests that targeted interventions for social cognition may also result in parallel improvement in some specific negative symptoms.

Ten-year trajectory and outcomes of negative symptoms of patients with first-episode schizophrenia spectrum disorders

2020 ◽  
Vol 220 ◽  
pp. 85-91
Author(s):  
Sherry Kit Wa Chan ◽  
Hei Yan Veronica Chan ◽  
Herbert H. Pang ◽  
Christy Lai Ming Hui ◽  
Yi Nam Suen ◽  
...  
Keyword(s):  
Negative Symptoms ◽  
First Episode ◽  
Schizophrenia Spectrum Disorders ◽  
Schizophrenia Spectrum ◽  
Spectrum Disorders ◽  
First Episode Schizophrenia

scholarly journals Acoustic speech markers for schizophrenia-spectrum disorders: a diagnostic and symptom-recognition tool

2021 ◽  
pp. 1-11
Author(s):  
J. N. de Boer ◽  
A. E. Voppel ◽  
S. G. Brederoo ◽  
H. G. Schnack ◽  
K. P. Truong ◽  
...  
Keyword(s):  
Negative Symptoms ◽  
Structured Interview ◽  
Diagnostic Value ◽  
Spectrum Disorder ◽  
Psychotic Symptoms ◽  
Schizophrenia Spectrum Disorders ◽  
Schizophrenia Spectrum Disorder ◽  
Speech Technology ◽  
Schizophrenia Spectrum ◽  
Spectrum Disorders

Abstract Background Clinicians routinely use impressions of speech as an element of mental status examination. In schizophrenia-spectrum disorders, descriptions of speech are used to assess the severity of psychotic symptoms. In the current study, we assessed the diagnostic value of acoustic speech parameters in schizophrenia-spectrum disorders, as well as its value in recognizing positive and negative symptoms. Methods Speech was obtained from 142 patients with a schizophrenia-spectrum disorder and 142 matched controls during a semi-structured interview on neutral topics. Patients were categorized as having predominantly positive or negative symptoms using the Positive and Negative Syndrome Scale (PANSS). Acoustic parameters were extracted with OpenSMILE, employing the extended Geneva Acoustic Minimalistic Parameter Set, which includes standardized analyses of pitch (F0), speech quality and pauses. Speech parameters were fed into a random forest algorithm with leave-ten-out cross-validation to assess their value for a schizophrenia-spectrum diagnosis, and PANSS subtype recognition. Results The machine-learning speech classifier attained an accuracy of 86.2% in classifying patients with a schizophrenia-spectrum disorder and controls on speech parameters alone. Patients with predominantly positive v. negative symptoms could be classified with an accuracy of 74.2%. Conclusions Our results show that automatically extracted speech parameters can be used to accurately classify patients with a schizophrenia-spectrum disorder and healthy controls, as well as differentiate between patients with predominantly positive v. negatives symptoms. Thus, the field of speech technology has provided a standardized, powerful tool that has high potential for clinical applications in diagnosis and differentiation, given its ease of comparison and replication across samples.

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